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Bridging Resolution: A Survey of the State of the Art

Summary

Bridging resolution connects an anaphor to an antecedent that is related to it but does not refer to the same entity. In the paper's example, "the games" depends on "baseball". The task is harder than entity coreference. It lacks agreement, syntactic or lexical-overlap cues, it often requires context and commonsense reasoning, and antecedents can be verb phrases or clauses as well as NPs. Kobayashi and Ng survey the field. They trace how the definition changed: identity relations were gradually removed, indefinite anaphors became allowed, and fixed relation inventories were abandoned. They also compare the main English corpora, list non-English resources, and review evaluation settings and published systems. They find the field fragmented. Corpora use different bridging definitions and often have no standard splits. Systems are evaluated with inconsistent filtering and gold inputs, and many are not released, so results are hard to compare. Reported scores are low, so the problem remains far from solved. The authors recommend:

  • a CoNLL-style benchmark with a much larger corpus;
  • collaboration with lexical-semantics and IE researchers;
  • end-to-end and hybrid models;
  • multilingual work using projection.

Key points

  • Main English corpora:
    • ISNotes: 50 WSJ docs, 663 anaphors.
    • BASHI: 50 WSJ docs, 459 anaphors.
    • ARRAU: domains RST (413 docs, 3777 anaphors), GNOME, PEAR and TRAINS.
    • SciCorp: 14 docs, 1366 anaphors, definite NPs only.
  • Differences between corpora: Most of the bridging annotated in ARRAU is lexical, whereas ISNotes, BASHI and SciCorp contain referential bridging. ISNotes excludes comparative anaphora, whereas BASHI and ARRAU treat it as bridging.
  • Evaluation settings: there are three, ranging from fully end-to-end to settings that supply gold mentions or gold anaphors. No existing resolver has been evaluated end-to-end.
  • Results: the best accuracy when resolving given anaphors is around 50%. The best resolution F-score in full bridging resolution is below 25%. Yu and Poesio's (2020) MTL model outperforms Rösiger et al.'s (2018b) rule-based system on ARRAU and ISNotes, but not on BASHI.
  • Non-English resources:
    • DIRNDL and GRAIN (German)
    • Prague Dependency Treebank (Czech)
    • RuGenBridge (Russian)
    • parallel corpora CorefPro (German–English–Russian) and Copenhagen Dependency Treebank

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

Fields: Linguistics & languages

Topics: Coreference resolution

Cited by

13 papers of our library cite it (of the 140673 whose bibliographies we read); 2 of them have a page here, 11 not yet.

Cite

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.18653/v1/2020.coling-main.331

@inproceedings{kobayashi2020bridging,
  title = {{Bridging Resolution: A Survey of the State of the Art}},
  author = {Kobayashi, Hideo and Ng, Vincent},
  booktitle = {Proceedings of the 28th International Conference on Computational Linguistics},
  year = {2020},
  doi = {10.18653/v1/2020.coling-main.331},
  url = {https://doi.org/10.18653/v1/2020.coling-main.331}
}

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